Best AI papers explained

481 Episodes

1. Converging Predictions with Shared Information

   Published: 5/11/2025
2. Test-Time Alignment Via Hypothesis Reweighting

   Published: 5/11/2025
3. Rethinking Diverse Human Preference Learning through Principal Component Analysis

   Published: 5/11/2025
4. Active Statistical Inference

   Published: 5/10/2025
5. Data Mixture Optimization: A Multi-fidelity Multi-scale Bayesian Framework

   Published: 5/10/2025
6. AI-Powered Bayesian Inference

   Published: 5/10/2025
7. Can Unconfident LLM Annotations Be Used for Confident Conclusions?

   Published: 5/9/2025
8. Predictions as Surrogates: Revisiting Surrogate Outcomes in the Age of AI

   Published: 5/9/2025
9. Learn then Test: Calibrating Predictive Algorithms to Achieve Risk Control

   Published: 5/9/2025
10. How to Evaluate Reward Models for RLHF

    Published: 5/9/2025
11. LLMs as Judges: Survey of Evaluation Methods

    Published: 5/9/2025
12. The Alternative Annotator Test for LLM-as-a-Judge: How to Statistically Justify Replacing Human Annotators with LLMs

    Published: 5/9/2025
13. Limits to scalable evaluation at the frontier: LLM as Judge won’t beat twice the data

    Published: 5/9/2025
14. Stratified Prediction-Powered Inference for Hybrid Language Model Evaluation

    Published: 5/9/2025
15. Accelerating Unbiased LLM Evaluation via Synthetic Feedback

    Published: 5/9/2025
16. Prediction-Powered Statistical Inference Framework

    Published: 5/9/2025
17. Optimizing Chain-of-Thought Reasoners via Gradient Variance Minimization in Rejection Sampling and RL

    Published: 5/9/2025
18. RM-R1: Reward Modeling as Reasoning

    Published: 5/9/2025
19. Reexamining the Aleatoric and Epistemic Uncertainty Dichotomy

    Published: 5/8/2025
20. Decoding Claude Code: Terminal Agent for Developers

    Published: 5/7/2025